A multiphasic approach for describing serial height data of Fels children: a hexaphasic-logistic-additive growth model.

In this paper, we reported the results obtained from fitting a new growth model to serial height data of 80 Fels children. The model assumed that human height growth curves are due to the combined effects of six macroscopic logistic growth processes, each reaching the same asymptotic height value. It was named the Walker and Walker-Hexaphasic-Logistic-Additive (WWHLA) growth model. An advantage to using this model is that it allowed us to easily fit entire growth curves with 14 biologically interpretable parameters. We tested the model using a computerized nonlinear least squares technique. The results showed that the new model worked extremely well. The fits resulted in high R, R2, and adjusted R2 values, large F values, relatively low residual mean squares, Durbin-Watson statistics that were very close to 2, and relatively small standard error estimates for the model parameters. In addition, the normality and constant variance test passed for more than 95 percent of the children, and the graphs of the residuals essentially showed no model bias. The new model identified the six growth components or processes in both male and female growth curves. The processes were named according to when they reached their peak height velocity: neonatal, infantile, early-childhood, middle-childhood, late-childhood, and pubertal. Preliminary results suggest that the WWHLA model appears to be the best that is currently available at this time for describing the human growth curve.